3D T1-weighted Gradient Echo Research Articles

Improved Assessment of Longitudinal Spinal Cord Atrophy in Multiple Sclerosis Using a Registration-Based Approach: Relevance for Clinical Studies.

Reliable measurements of cervical cord atrophy progression may be useful for monitoring neurodegeneration in multiple sclerosis (MS). To compare a new, registration-based (Reg) method with two existing methods (active surface [AS] and propagation segmentation [PropSeg]) to measure cord atrophy changes over time in MS. Retrospective. Cohort I: Eight healthy controls (HC) and 28 MS patients enrolled at a single institution, and cohort II: 25 HC and 63 MS patients enrolled at three European sites. 3D T1-weighted gradient echo sequence, acquired at 1.5 T (cohort I) and 3.0 T (cohort II). Percentage cord area changes (PCACs) between baseline and follow-up (cohort I: 2.34 years [interquartile range=2.00-2.55 years], cohort II: 1.05 years [interquartile range=1.01-1.18 years]) were evaluated for all subjects using Reg, AS, and PropSeg. Reg included an accurate registration of baseline and follow-up straightened cord images, followed by AS-based optimized cord segmentation. A subset of studies was analyzed twice by two observers. Linear regression models were used to estimate annualized PCAC, and effect sizes expressed as the ratio between the estimated differences and HC error term (P < 0.05). Reproducibility was assessed by linear mixed-effect models. Annualized PCACs were used for sample size calculations (significance: α=0.05, power: 1 - β=0.80). Annualized PCACs and related standard errors (SEs) were lower with Reg than with other methods: PCAC in MS patients at 1.5 T was -1.12% (SE=0.22) with Reg, -1.32% (SE=0.30) with AS, and -1.40% (SE=0.33) with PropSeg, while at 3.0 T PCAC was -0.83% (SE=0.25) with Reg, -0.92% (SE=0.32) with AS, and -1.18 (SE=0.53) with PropSeg. This was reflected in larger effect sizes and lower sample sizes. Intra- and inter-observer agreement range was 0.72-0.91 with AS, and it was >0.96 with Reg. The results support the use of the registration method to measure cervical cord atrophy progression in future MS clinical studies. 3 TECHNICAL EFFICACY STAGE: 2.

Data-Driven Modification of the LI-RADS Major Feature System on Gadoxetate Disodium-Enhanced MRI: Toward Better Sensitivity and Simplicity.

The Liver Imaging Reporting and Data System (LI-RADS) is widely accepted as a reliable diagnostic scheme for hepatocellular carcinoma (HCC) in at-risk patients. However, its application is hampered by substantial complexity and suboptimal diagnostic sensitivity. To propose data-driven modifications to the LI-RADS version 2018 (v2018) major feature system (rLI-RADS) on gadoxetate disodium (EOB)-enhanced magnetic resonance imaging (MRI) to improve sensitivity and simplicity while maintaining high positive predictive value (PPV) for detecting HCC. Retrospective. Two hundred and twenty-four consecutive at-risk patients (training dataset: 169, independent testing dataset: 55) with 742 LR-3 to LR-5 liver observations (HCC: N=498 [67%]) were analyzed from a prospective observational registry collected between July 2015 and September 2018. 3.0 T/T2-weighted fast spin-echo, diffusion-weighted spin-echo based echo-planar and three-dimensional (3D) T1-weighted gradient echo sequences. All images were evaluated by three independent abdominal radiologists who were blinded to all clinical, pathological, and follow-up information. Composite reference standards of either histopathology or imaging follow-up were used. In the training dataset, LI-RADS v2018 major features were used to develop rLI-RADS based on their associated PPV for HCC. In an independent testing set, diagnostic performances of LI-RADS v2018 and rLI-RADS were computed using a generalized estimating equation model and compared with McNemar's test. A P value <0.05 was considered statistically significant. The median (interquartile range) size of liver observations was 13 mm (7-27 mm). The diagnostic table for rLI-RADS encompassed 9 cells, as opposed to 16 cells for LI-RADS v2018. In the testing set, compared to LI-RADS v2018, rLI-RADS category 5 demonstrated a significantly superior sensitivity (76% vs. 61%) while maintaining comparably high PPV (92.5% vs. 94.1%, P=0.126). Compared with LI-RADS v2018, rLI-RADS demonstrated improved simplicity and significantly superior diagnostic sensitivity for HCC in at-risk patients. 3 TECHNICAL EFFICACY STAGE: 2.

Optimal sequences and sequence parameters for GBCA-enhanced MRI of the glymphatic system: a systematic literature review

The glymphatic system (GS) is a recently discovered waste clearance system in the brain. To evaluate the most promising magnetic resonance imaging (MRI) sequence(s) and the most optimal sequence parameters for glymphatic MRI (gMRI) 4-24 h after administration of gadolinium-based contrast agent (GBCA). Multiple literature databases were systematically searched for articles regarding gMRI or MRI of the perilymph in the inner ear until 11 May 2020. All relevant MRI sequence parameters were tabulated for qualitative analysis. Their potential was assessed based on detection of low dose GBCA, primarily measured as signal intensity (SI) ratio. Thirty articles were included in the analysis. Three-dimensional fluid attenuated inversion recovery (3D-FLAIR), 3D Real Inversion Recovery (3D-Real IR), and multiple 3D T1-weighted gradient echo sequences were used. In perilymph, 3D-FLAIR with a TE of at least 400 ms yielded the highest SIRs. In the qualitative analysis of inner ear studies using 3D-FLAIR, TR was in the range of 4400-10,000 ms, TI 1500-2600 ms, refocusing flip angle (rFA) (range 120°-180°), and echo train length (ETL) 23-173. In the gMRI studies, quantitative analysis was not possible. In the qualitative analysis, 3D-FLAIR was used in the majority (8/12) of the studies, usually with TR 4800-9000 ms, TI 1650-2500 ms, TE 311-561 ms, rFA 90°-120°, and ETL 167-278. Long TE 3D-FLAIR is the most promising sequence for detection of low-dose GBCA in the GS. Clinical and/or phantom studies on other MRI parameters are needed for further optimization of gMRI.

MetNet: Computer-aided segmentation of brain metastases in post-contrast T1-weighted magnetic resonance imaging

PurposeBrain metastases are manually contoured during stereotactic radiosurgery (SRS) treatment planning, which is time-consuming, potentially challenging, and laborious. The purpose of this study was to develop and investigate a 2-stage deep learning (DL) approach (MetNet) for brain metastasis segmentation in pre-treatment magnetic resonance imaging (MRI). Materials and methodsWe retrospectively analyzed postcontrast 3D T1-weighted spoiled gradient echo MRIs from 934 patients who underwent SRS between August 2009 and August 2018. Neuroradiologists manually identified brain metastases in the MRIs. The treating radiation oncologist or physicist contoured the brain metastases. We constructed a 2-stage DL ensemble consisting of detection and segmentation models to segment the brain metastases on the MRIs. We evaluated the performance of MetNet by computing sensitivity, positive predictive value (PPV), and Dice similarity coefficient (DSC) with respect to metastasis size, as well as free-response receiver operating characteristics. ResultsThe 934 patients (mean [±standard deviation] age 59 ± 13 years, 474 women) were randomly split into 80% training and 20% testing groups (748:186). For patients with metastases 1–52 mm (n = 766), 648 (85%) were detected and segmented with a mean segmentation DSC of 81% ± 15%. Patient-averaged sensitivity was 88% ± 19%, PPV was 58% ± 25%, and DSC was 85% ± 13% with 3 ± 3 false positives (FPs) per patient. When considering only metastases ≥6 mm, patient-averaged sensitivity was 99% ± 5%, PPV was 67% ± 28%, and DSC was 87% ± 13% with 1 ± 2 FPs per patient. ConclusionMetNet can segment brain metastases across a broad range of metastasis sizes with high sensitivity, low FPs, and high segmentation accuracy in postcontrast T1-weighted MRI, potentially aiding treatment planning for SRS.

Deep learning LI-RADS grading system based on contrast enhanced multiphase MRI for differentiation between LR-3 and LR-4/LR-5 liver tumors.

BackgroundTo develop a deep learning (DL) method based on multiphase, contrast-enhanced (CE) magnetic resonance imaging (MRI) to distinguish Liver Imaging Reporting and Data System (LI-RADS) grade 3 (LR-3) liver tumors from combined higher-grades 4 and 5 (LR-4/LR-5) tumors for hepatocellular carcinoma (HCC) diagnosis.MethodsA total of 89 untreated LI-RADS-graded liver tumors (35 LR-3, 14 LR-4, and 40 LR-5) were identified based on the radiology MRI interpretation reports. Multiphase 3D T1-weighted gradient echo imaging was acquired at six time points: pre-contrast, four phases immediately post-contrast, and one hepatobiliary phase after intravenous injection of gadoxetate disodium. Image co-registration was performed across all phases on the center tumor slice to correct motion. A rectangular tumor box centered on the tumor area was drawn to extract subset tumor images for each imaging phase, which were used as the inputs to a convolutional neural network (CNN). The pre-trained AlexNet CNN model underwent transfer learning using liver MRI data for LI-RADS tumor grade classification. The output probability number closer to 1 or 0 indicated a higher possibility of being combined LR-4/LR-5 tumor or LR-3 tumor, respectively. Five-fold cross validation was used for training (60% dataset), validation (20%) and testing processes (20%).ResultsThe DL CNN model for LI-RADS grading using inputs of multiphase liver MRI data acquired at three time points (pre-contrast, arterial, and washout phase) achieved a high accuracy of 0.90, sensitivity of 1.0, precision of 0.835, and AUC of 0.95 with reference to the expert human radiologist report. The CNN output of probability provided radiologists a confidence level of the model’s grading for each liver lesion.ConclusionsAn AlexNet CNN model for LI-RADS grading of liver lesions provided diagnostic performance comparable to radiologists and offered valuable clinical guidance for differentiating intermediate LR-3 liver lesions from more-likely malignant LR-4/LR-5 lesions in HCC diagnosis.

Shortening the acquisition time of whole-body MRI: 3D T1 gradient echo Dixon vs fast spin echo for metastatic screening in prostate cancer.

To compare 3D T1-weighted fast spin echo (FSE) and 3D T1-weighted gradient echo (GE) mDixon as morphologic sequences to complement diffusion-weighted imaging (DWI) for the metastatic screening in prostate cancer (PCa) patients. Thirty PCa patients at high risk of metastases prospectively underwent both a 3D T1 FSE (14 min) and a rapid 3D T1 GEmDixon (1 min 20 s) sequences within a WB-MRI protocol. Two readers assessed the diagnostic performance of the FSE/Fat/in-phase (IP)/IP+Fat sequences in detecting bone and node metastases. The reference standard was established by a panel of four physicians on the basis of all baseline and follow-up imaging, biological and clinical information. The reproducibility of readings, predictive accuracy (Acc) from ROC curves analysis, and contrast-to-reference ratio (CRR) in lesions were assessed for each sequence. In bone and lymph nodes (per-region analysis), reproducibility was at least good for all sequences/readers, except for nodes in the common iliac/inguinal regions. In bone (per-organ analysis), Acc of FSE was superior to that of mDixon (difference + 4%, p < 0.0083). In nodes (per-organ analysis), Acc of Fat was superior to that of other sequences (difference + 4% to + 6% depending on reader, p < 0.0083). In the per-patient analysis, Acc of FSE was superior to that of mDixon (difference + 4% to + 6% depending on sequence, p < 0.0083). Fat images had higher CRR compared with FSE in the thoracic spine, the bony pelvis and lymph node metastases (p < 0.025). 3D T1 GEmDixon may replace 3D T1 FSE to complement DWI in WB-MRI for metastatic screening in PCa. It demonstrates an Acc ranging from + 4% to + 6% (nodes) to - 4% to - 6% (bone and patient staging) compared with FSE and considerably reduces the examination time, offering the perspective of acquiring WB-MRI examinations in less than 20 min. • The replacement of 3D T1 FSE by the 3D T1 GE mDixon as morphologic sequence to complement DWI drastically reduces the acquisition time of WB-MRI studies. • The 3D T1 GE mDixon sequence offers similar reproducibility of image readings compared with that of the 3D T1 FSE. • Differences in diagnostic accuracy are limited (+ 4%/+ 6% in favor of mDixon to detect node metastases; + 4%/+ 6% in favor of FSE to detect bone metastases/metastatic disease in a patient).

Consensus recommendations for a standardized brain tumor imaging protocol for clinical trials in brain metastases.

A recent meeting was held on March 22, 2019, among the FDA, clinical scientists, pharmaceutical and biotech companies, clinical trials cooperative groups, and patient advocacy groups to discuss challenges and potential solutions for increasing development of therapeutics for central nervous system metastases. A key issue identified at this meeting was the need for consistent tumor measurement for reliable tumor response assessment, including the first step of standardized image acquisition with an MRI protocol that could be implemented in multicenter studies aimed at testing new therapeutics. This document builds upon previous consensus recommendations for a standardized brain tumor imaging protocol (BTIP) in high-grade gliomas and defines a protocol for brain metastases (BTIP-BM) that addresses unique challenges associated with assessment of CNS metastases. The "minimum standard" recommended pulse sequences include: (i) parameter matched pre- and post-contrast inversion recovery (IR)-prepared, isotropic 3D T1-weighted gradient echo (IR-GRE); (ii) axial 2D T2-weighted turbo spin echo acquired after injection of gadolinium-based contrast agent and before post-contrast 3D T1-weighted images; (iii) axial 2D or 3D T2-weighted fluid attenuated inversion recovery; (iv) axial 2D, 3-directional diffusion-weighted images; and (v) post-contrast 2D T1-weighted spin echo images for increased lesion conspicuity. Recommended sequence parameters are provided for both 1.5T and 3T MR systems. An "ideal" protocol is also provided, which replaces IR-GRE with 3D TSE T1-weighted imaging pre- and post-gadolinium, and is best performed at 3T, for which dynamic susceptibility contrast perfusion is included. Recommended perfusion parameters are given.

Machine Learning Based Detection of Brain Cancer Metastases in MR Images for Stereotactic Radiosurgery Using Single-Shot Detectors

Identification of brain cancer metastases in MR images for stereotactic radiation treatment is presently performed manually by a radiologist/radiation oncologist and can be time-consuming. The purpose of this study was to investigate machine learning based single-shot detectors (SSDs) for automatic detection of brain metastases. Post-contrast 3D T1-weighted gradient echo images (FOV=24 cm, TR/TE=6.947/2.428 ms, voxel size=0.94×0.94×1.00 mm) from 146 patients who underwent noninvasive stereotactic radiosurgery at our institution were included in the study. The manual identification and contouring of the brain metastases by neuroradiologists and treating radiation oncologists were used as the ground truth. The patients were partitioned into 3 cohorts of 99/25/22 for training/validation/testing purposes with a total of 438/117/93 brain metastases, respectively. The size of the brain metastases ranged from 1.88 to 50.63 mm and was distributed similarly in the 3 cohorts. We constructed a multibox SSD with 16 convolutional layers, of which 6 layers of different resolution scales (128×128, 64×64, 32×32, 16×16, 8×8 and 6×6) were used for prediction. We used the SSD loss function with a weighted sum between the localization loss (Smooth L1) and the classification loss (Softmax). Inputs to the network were the axial slices of the MR images, and the outputs were the bounding box coordinates and the associated confidence of the classifier. An Adam optimizer was used to train the network and the initial learning rate was set to 2×10-4. Random affine transformation augmentations, decayed learning rates and an early stopping scheme were applied during the training procedure. The detection performance was analyzed on 11 different confidence thresholds ranging from 99% to 0%. For each threshold, the predicted volumes of interest were reconstructed using the output bounding box coordinates and were compared with the ground truth. True positives (TPs) were defined as predictions having at least one voxel overlap with the ground truth bounding box; otherwise, they were considered false positives (FPs). An average sensitivity of 73.5% and FP/TP ratio of 15.8 were achieved across all sizes of brain metastases and all confidence thresholds. For metastases ≥6 mm, the average sensitivity was 94.5%, and the FP/TP ratio was 7.9. Detection performance for 30%, 60%, and 90% confidence thresholds are listed in Table 1. The SSD was able to detect almost all brain metastases ≥6 mm with high confidence and specificity, and nearly half the metastases <6mm with low specificity. The performance of the model is expected to further improve through ablation studies, hyperparameter searches, and inclusion of additional curated patient data.Abstract 1002; Table 1Detection performance of the SSD for 3 confidence thresholds.Confidence threshold<6 mm≥6 mmSensitivityFP/TP ratioSensitivityFP/TP ratio90%33.3%1.7190.2%0.9160%42.9%3.0696.1%1.8230%54.8%5.8796.1%3.69 Open table in a new tab

Update on MR imaging of the pulmonary vasculature

Magnetic resonance imaging (MRI) plays an increasingly important role in the non-invasive evaluation of the pulmonary vasculature. MR angiographic (MRA) techniques provide morphological information, while MR perfusion techniques provide functional information of the pulmonary vasculature. Contrast-enhanced MRA can be performed at high spatial resolution using 3D T1-weighted spoiled gradient echo sequence or at high temporal resolution using time-resolved techniques. Non-contrast MRA can be performed using 3D steady state free precession, double inversion fast spin echo, time of flight or phase contrast sequences. MR perfusion can be done using dynamic contrast-enhanced technique or using non-contrast techniques such as arterial spin labelling and time-resolved imaging of lungs during free breathing with Fourier decomposition analysis. MRI is used in the evaluation of acute and chronic pulmonary embolism, pulmonary hypertension and other vascular abnormalities, congenital anomalies and neoplasms. In this article, we review the different MR techniques used in the evaluation of pulmonary vasculature and its clinical applications.

Combination of free-breathing radial 3D fat-suppressed T1-weighted gradient-echo sequence with diffusion weighted images: Potential for differentiating malignant from benign peripheral solid pulmonary masses

ObjectivesHigh resolution CT is the most commonly used radiological method for differentiating benign from malignant peripheral solid pulmonary masses, however, some of them are not easily diagnosed by morphology alone. Furthermore, due to the radiation dose, it is unsuitable for patients with disorders requiring repeated examinations over prolonged periods. The aims of this study were to evaluate whether a combination of diffusion-weighted images (DWI) and free-breathing radial 3D fat-suppressed T1-weighted gradient echo (radial volumetric interpolated breath-hold examination, radial VIBE) sequence can enable discrimination between benign from malignant peripheral solid pulmonary masses. Materials and methodsBoth chest CT scan and MR imaging with radial VIBE and DWI were obtained from 47 patients; 30 males and 17 females (mean age 64 years old; age range 48–83 years old). Benign and malignant peripheral solid pulmonary masses were conclusively identified by pathology results. Two radiologists independently reviewed all the images and record radiological features including morphological signs on radial VIBE, CT images, and ADC value. Receiver operating characteristic (ROC) was used to analyze the capability of radial VIBE as well as DWI to distinguish malignant from benign peripheral solid pulmonary masses. ResultsIn 77% of patients, malignant peripheral solid pulmonary masses were found. Morphological signs of mediastinal lymph node enlargement and lobulation were more easily found in malignant masses in both radial VIBE (mediastinal lymph node enlargement: p = 0.033, lobulation: p = 0.039) and CT (mediastinal lymph node enlargement: p = 0.004, lobulation: p = 0.012). The ADC value were also significant difference between benign and malignant groups (p = 0.001). Combined ADC value with radial VIBE was a most specific test than routine-dose CT (86.1% vs 75%, p < 0.001), but less sensitive than routine-dose CT (81.8% vs 90.9%; p < 0.001) for malignant peripheral solid pulmonary masses detection. Diagnostic accuracy was 89% for combining ADC value with radial VIBE, and 85% for routine-dose CT. ConclusionsCombination of morphological signs and ADC value seems to improve differentiating malignant from benign peripheral solid pulmonary masses. Especially in patients unable to endure radiation exposure, suspend respiration, radial VIBE provides similar morphological signs displaying to those on routine-dose CT.

Correlation of DNA ploidy and cell cycle analysis with diffusion tensor and dynamic susceptibility contrast MRI metrics in meningiomas

Purpose: To investigate the relationship between diffusion tensor imaging and dynamic susceptibility perfusion MRI metrics with cell cycle analysis findings in meningiomas. Material and Methods: Fourteen patients (4 men, 10 women, aged 30-76 years; median 58 years) with meningiomas were included in the study. There were 9 grade I and 5 grade II meningiomas. The MRI protocol consisted of T2-weighted turbo spin echo, unenhanced and contrast enhanced T1-weighted 3D spoiled gradient echo sequences. Diffusion tensor imaging (DTI) metrics, such as apparent diffusion coefficient (ADC) and fractional anisotropy (FA), were assessed with a single shot, multi-slice, spin-echo planar sequence (max b-value: 700 sec/mm²) and dynamic susceptibility perfusion imaging (DSC) metrics, such as the relative cerebral blood volume (rCBV), with a T2* gradient-echo, multishot echo planar imaging sequence. DNA ploidy and cell cycle analysis was analysed by flow cytometry. Results: There was a significant negative correlation between rCBV and G0/G1 phase fraction ( r =−0.791, p =0.004) and a positive correlation with G2/M phase fraction ( r =0.621, p =0.04). A significant correlation was also observed between FA ratio and G0/G1 phase fraction ( r =0.721, p =0.018). No significant correlation was found between G0/G1, S-phase, G2/M and ADC values. Conclusions: DSC MRI and DTI metrics are correlated to meningioma aggressiveness as assessed by cell cycle analysis.

Multiparametric MRI Characterization of Funaki Types of Uterine Fibroids Considered for MR-Guided High-Intensity Focused Ultrasound (MR-HIFU) Therapy

To compare quantitative multiparametric magnetic resonance imaging (mpMRI) data of symptomatic uterine fibroids being considered for MR-guided high-intensity focused ultrasound ablation with fibroid characterization based on the Funaki Classification scheme. This was a prospective, Institutional Review Board -approved, Health Insurance Portability, and Accountability Act-compliant study. Informed consent was obtained. From December 2013 to April 2015, 48 women with symptomatic fibroids underwent screening with mpMRI protocol including sagittal/axial T2-weighted fast spin-echo, sagittal diffusion-weighted, and sagittal dynamic contrast-enhanced 3D T1-weighted gradient echo imaging on a 3T magnet. All fibroids were assigned Funaki type 1, 2, or 3 based on T2-weighted imaging. Differences in size, perfusion, and diffusion/intravoxel incoherent motion parameters among the three Funaki types were determined using linear mixed model. A logistic regression analysis was performed to select the best model in predicting type 3 fibroids. A total of 100 fibroids were assessed (20 type 1, 66 type 2, and 14 type 3). Apparent diffusion coefficient and D of type 3 fibroids were significantly higher than those of type 1 (P < 0.0001, P < 0.0001) and 2 fibroids (P = 0.004, P < 0.0001) respectively. Transfer constant of type 3 fibroids was significantly higher than type 1 (P = 0.0357), but not than type 2 (P = 0.0752). A cutoff value of D = 1 × 10-3 mm2/s offers an accuracy, sensitivity, and specificity of 76%, 71%, and 77%, respectively, for the diagnosis of Funaki 3 fibroids. mpMRI-derived quantitative parameters may enable a more objective selection of patients prior to MR-guided high-intensity focused ultrasound therapy.

Comparison of four dimensional computed tomography and magnetic resonance imaging in abdominal radiotherapy planning.

Background and PurposeFour-dimensional (4D) computed tomography (CT) is widely used in radiotherapy (RT) planning and remains the current standard for motion evaluation. We assess a 4D magnetic resonance imaging (MRI) sequence in terms of motion and image quality in a phantom, healthy volunteers and patients undergoing RT.Materials and MethodsThe 4D-MRI sequence is a prototype T1-weighted 3D gradient echo with radial acquisition with self-gating. The accuracy of the 4D-MRI respiratory sorting based method was assessed using a MRI-CT compatible respiratory simulation phantom. In volunteers, abdominal viscera were evaluated for artefact, noise, structure delineation and overall image quality using a previously published four-point scoring system. In patients undergoing abdominal RT, the tumour (or a surrogate) was utilized to assess the range of motion on both 4D-CT and 4D-MRI. Furthermore, imaging quality was evaluated for both 4D-CT and 4D-MRI.ResultsIn phantom studies 4D-MRI demonstrated amplitude of motion error of less than 0.2 mm for five, seven and ten bins. 4D-MRI provided excellent image quality for liver, kidney and pancreas. In patients, the median amplitude of motion seen on 4D-CT and 4D-MRI was 11.2 mm (range 2.8–20.3 mm) and 10.1 mm (range 0.7–20.7 mm) respectively. The median difference in amplitude between 4D-CT and 4D-MRI was −0.6 mm (range −3.4–5.2 mm). 4D-MRI demonstrated superior edge detection (median score 3 versus 1) and overall image quality (median score 2 versus 1) compared to 4D-CT.ConclusionsThe prototype 4D-MRI sequence demonstrated promising results and may be used in abdominal targeting, motion gating, and towards implementing MRI-based adaptive RT.

7 Tesla MRI of Balo's concentric sclerosis versus multiple sclerosis lesions.

BackgroundBaló's concentric sclerosis (BCS) is a rare condition characterized by concentrically layered white matter lesions. While its pathogenesis is unknown, hypoxia‐induced tissue injury and chemotactic stimuli have been proposed as potential causes of BCS lesion formation. BCS has been suggested to be a variant of multiple sclerosis (MS). Here, we aimed to elucidate similarities and differences between BCS and MS by describing lesion morphology and localization in high‐resolution 7 Tesla (7 T) magnetic resonance imaging (MRI) scans.MethodsTen patients with Baló‐type lesions underwent 7 T MRI, and 10 relapsing remitting MS patients served as controls. The 7 T MR imaging protocol included 3D T1‐weighted (T1w) magnetization‐prepared rapid gradient echo, 2D high spatial resolution T2*‐weighted (T2*w) fast low‐angle shot and susceptibility‐weighted imaging.ResultsIntralesional veins were visible in the center of all but one Baló‐type lesion. Four Baló‐type lesions displayed inhomogeneous intralesional T2*w signal intensities, which are suggestive of microhemorrhages or small ectatic venules. Eight of 10 BCS patients presented with 97 additional lesions, 36 of which (37%) had a central vein. Lesions involving the cortical gray matter and the U‐fibers were not detected in BCS patients.ConclusionOur findings support the hypothesis that BCS and MS share common pathogenetic mechanisms but patients present with different lesion phenotypes.

Correlation of Longitudinal Gray Matter Volume Changes and Motor Recovery in Patients After Pontine Infarction.

The mechanisms of motor functional recovery after pontine infarction (PI) remain unclear. Here, we assessed longitudinal changes in gray matter volume (GMV) and examined the relationship between GMV and clinical outcome. Fifteen patients with unilateral PI underwent magnetic resonance imaging and neurological exams five times during a period of 6 months. Another 15 healthy participants were enrolled as the normal control (NC) group and were examined with the same protocol. The MR exam included routine protocol and a 3D T1-weighted magnetization-prepared rapid acquisition gradient echo scan. Changes in GMV were assessed using voxel-based morphometry. Furthermore, the correlations between GMV changes in regions of interest and clinical scores were assessed. Compared with NCs, the decreased GMVs in the contralateral uvula of cerebellum and the ipsilateral tuber of cerebellum were detected at third month after stroke onset. At the sixth month after stroke onset, the decreased GMVs were detected in the contralateral culmen of cerebellum, putamen, as well as in the ipsilateral tuber/tonsil of cerebellum. Compared with NC, the PI group exhibited significant increases in GMV at each follow-up time point relative to stroke onset. Specifically, the significant GMV increase was found in the ipsilateral middle frontal gyrus and ventral anterior nucleus of thalamus at second week after stroke onset. At first month after stroke onset, the increased GMVs in the ipsilateral middle temporal gyrus were detected. The significant GMV increase in the ipsilateral mediodorsal thalamus was noted at third month after stroke onset. At the end of sixth month after stroke onset, the GMV increase was found in the ipsilateral mediodorsal thalamus, superior frontal gyrus, and the contralateral precuneus. Across five times during a period of 6-month, a negative correlation was observed between mean GMV in the contralateral uvula, culmen, putamen, and ipsilateral tuber/tonsil and mean Fugl-Meyer (FM) score. However, mean GMV in the ipsilateral mediodorsal thalamus was positively correlated with mean FM score. Our findings suggest that structural reorganization of the ipsilateral mediodorsal thalamus might contribute to motor functional recovery after PI.

Contrast-enhanced magnetic resonance imaging for the detection of ruptured coronary plaques in patients with acute myocardial infarction.

PurposeX-ray coronary angiography (XCA) is the current gold standard for the assessment of lumen encroaching coronary stenosis but XCA does not allow for early detection of rupture-prone vulnerable plaques, which are thought to be the precursor lesions of most acute myocardial infarctions (AMI) and sudden death. The aim of this study was to investigate the potential of delayed contrast-enhanced magnetic resonance coronary vessel wall imaging (CE-MRCVI) for the detection of culprit lesions in the coronary arteries.Methods16 patients (13 male, age 61.9±8.6 years) presenting with sub-acute MI underwent CE-MRCVI within 24-72h prior to invasive XCA. CE-MRCVI was performed using a T1-weighted 3D gradient echo inversion recovery sequence (3D IR TFE) 40±4 minutes following the administration of 0.2 mmol/kg gadolinium-diethylenetriamine-pentaacetic acid (DTPA) on a 3T MRI scanner equipped with a 32-channel cardiac coil.Results14 patients were found to have culprit lesions (7x LAD, 1xLCX, 6xRCA) as identified by XCA. Quantitative CE-MRCVI correctly identified the culprit lesion location with a sensitivity of 79% and excluded culprit lesion formation with a specificity of 99%. The contrast to noise ratio (CNR) of culprit lesions (9.7±4.1) significantly exceeded CNR values of segments without culprit lesions (2.9±1.9, p<0.001).ConclusionCE-MRCVI allows the selective visualization of culprit lesions in patients immediately after myocardial infarction (MI). The pronounced contrast uptake in ruptured plaques may represent a surrogate biomarker of plaque activity and/or vulnerability.

Long-Term Blood Brain Barrier Permeability Changes After Radiosurgery and Immunotherapy for Melanoma Brain Metastases

In the era of immunotherapy (IT) and longer patient survival, differentiating radiation necrosis (RN) from recurrent or progressive tumor (RPT) is a major diagnostic challenge due to similar appearance on MRI. Ktrans is a value calculated from dynamic contrast enhanced (DCE) MRIs correlating with vascular permeability, such as the breakdown of the blood brain barrier (BBB). The value of ktrans can be elevated above baseline (<0.04 min-1) with either RPT (>3.6 min-1) or RN. The purpose of this study was to investigate the pattern of ktrans changes in patients receiving SRS and IT with the hope of utilizing ktrans to help distinguish RN from RPT. We retrospectively reviewed DCE brain MRIs of 10 patients with melanoma brain metastases (MBM) following treatment with SRS and IT. 3D T1-weighted spoiled gradient echo DCE perfusion imaging was performed on a 3-Tesla MRI. Ktrans was measured using FDA approved software (OleaSphere, Olea Medical Solutions Inc Cambridge, MA). A region of interest was placed on T1 enhancing tissue on ktrans maps fused with T1 post-contrast images. A mean ktrans was assigned to each lesion on each scan over time, and the highest (mean) value was used for this analysis. A binary logistic regression to evaluate the post-treatment correlation of the ktrans value with RN was performed. A median of 4.5 cycles of ipilimumab were delivered (range 2-14) with a median of 21Gy (16-24Gy). A median of 2.5 DCE images per patient were reviewed (range 1-7), and these were acquired at a median of 17.9 months after SRS (range 0.9-87 months). The median follow up for this group of 10 patients was 32 months (range 5.4-80 months), and the mean survival was 63 months (95% CI 44-82).The median ktrans(mean) for all patients who received SRS/IT was found to be elevated above baseline at 0.35 min-1 (range 0.13-4.57 min-1). Six of 10 patients also had radiographic evidence of RN [3/6 pathologically proven] diagnosed at a median of 11.9 months after SRS (range 3.6-65.1months). The peak ktrans was seen at 24.7 months after SRS in patients with RN vs 17.9 months in those without RN (p=0.156). Patients with RN had peak ktrans(mean) value of 0.42 min-1 vs 0.285 min-1 in those without RN (p=0.12). This small, preliminary study shows that ktransmean for patients treated with SRS and IT continues to evolve after radiographic diagnosis of RN and peaks at 24.7 months after SRS. The value of ktrans trends higher in those with RN (0.42 min-1 vs 0.285min-1), but it was not statistically significant. This is the first study to investigate the long-term change in ktrans (permeability) after radiosurgery and immunotherapy. This information may be valuable when deciding on the management of enlarging brain metastases in the setting of immunotherapy.

Dynamic Volume Assessment of Hepatocellular Carcinoma in Rat Livers Using a Clinical 3T MRI and Novel Segmentation

ABSTRACTPurpose: In vivo liver cancer research commonly uses rodent models. One of the limitations of such models is the lack of accurate and reproducible endpoints for a dynamic assessment of growing tumor nodules. The aim of this study was to validate a noninvasive, true volume segmentation method using two rat hepatocellular carcinoma (HCC) models, correlating magnetic resonance imaging (MRI) with histological volume measurement, and with blood levels of α-fetoprotein. Materials and methods: We used 3T clinical MRI to quantify tumor volume with follow-up over time. Using two distinct rat HCC models, calculated MRI tumor volumes were correlated with volumes from histological sections, or with blood levels of α-fetoprotein. Eleven rats, comprising six Buffalo rats (n = 9 scans) and five Fischer rats (n = 14 tumors), were injected in the portal vein with 2.5 × 105 and 2.0 × 106 syngeneic HCC cells, respectively. Longitudinal (T1) relaxation time- and transverse (T2) relaxation time-weighted MR images were acquired. Results: The three-dimensional (3D) T1-weighted gradient echo had 0.35-mm isotropic resolution allowing accurate semi-automatic volume segmentation. 2D T2-weighted imaging provided high tumor contrast. Segmentation of combined 3D gradient echo T1-weighted images and 2D turbo spin echo T2-weighted images provided excellent correlation with histology (y = 0.866x + 0.034, R² = 0.997 p < .0001) and with α-fetoprotein (y = 0.736x + 1.077, R² = 0.976, p < .0001). There was robust inter- and intra-observer reproducibility (intra-class correlation coefficient > 0.998, p < .0001). Conclusions: We have developed a novel, noninvasive contrast imaging protocol which enables semi-automatic 3D volume quantification to analyze nonspherical tumor nodules and to follow up the growth of tumor nodules over time.

Evaluation of deep gray matter volume, cortical thickness and white matter integrity in patients with typical absence epilepsy: a study using voxelwise-based techniques.

The objective of this study was to evaluate the cortical thickness and the volume of deep gray matter structures, measured from 3D T1-weighted gradient echo imaging, and white matter integrity, by diffusion tensor imaging (DTI) in patients with typical absence epilepsy (AE). Patients (n=19) with typical childhood AE and juvenile AE, currently taking antiepileptic medication, were compared with control subjects (n=19), matched for gender and age. 3D T1 magnetization-prepared rapid gradient echo-weighted imaging and DTI along 30 noncolinear directions were performed using a 1.5-T MR scanner. FreeSurfer was used to perform cortical volumetric reconstruction and segmentation of deep gray matter structures. For tract-based spatial statistics analysis of DTI, a white matter skeleton was created, along with a permutation-based inference with 5000 permutations. A threshold of p<0.05 was used to identify abnormalities in fractional anisotropy (FA). The mean, radial, and axial diffusivities were also projected onto the mean FA skeleton. Patients with AE presented decreased FA and increased mean diffusivity and radial diffusivity values in the genu and the body of the corpus callosum and right anterior corona radiata, as well as decreased axial diffusivity in the left posterior thalamic radiation, inferior cerebellar peduncle, right cerebral peduncle, and right corticospinal tract. However, there were no significant differences in cortical thickness or deep gray matter structure volumes between patients with AE and controls. Abnormalities found in white matter integrity may help to better understand the pathophysiology of AE and optimize diagnosis and treatment strategies.

基于表面的形态测量学：3T与7T高分辨磁共振结构成像受试者内比较

ObjectiveHigh resolution structural MR imaging can reveal structural characteristics of cerebral cortex and provide an insight into normal brain development and neuropsychological diseases. The aim of this study was to compare cortical structural characteristics of normal human brain between 3T and 7T MRI systems using surface-based morphometry based on high resolution structural MR imaging. Methods Twelve healthy volunteers were scanned by both 3T with 3D T1-weighted fast spoiled gradient recalled echo (3D T1-FSPGR) sequence and 7T with 3D T1-weighted magnetization-prepared rapid gradient echo (3D T1-MPRAGE) sequence. MRI data were processed with FreeSurfer. The cortical thickness, white and gray matter surface area, convexity, and curvature from data of 3T and 7T were measured and compared by paired t-test. Results Measurements of mean cortical thickness, total white matter surface area and gray matter surface area of 3T were larger than those of 7T (left hemisphere: P=0.000, 0.006, 0.020 respectively; right hemisphere: P=0.000, 0.000, 0.000 respectively). Surface-based morphometry over the whole brain demonstrated both reduced and increased measurements of cortical thickness, white and gray surface area, convexity, and curvature at 7T compared to 3T. Conclusions Inconsistency of brain structural attribute between 3T and 7T was confirmed, and researchers should be cautious about data when using ultrahigh field MR system to investigate brain structural changes.